Prognosis Of Melanoma Patients Research Articles

Identification of biomarkers associated with melanoma based on bioinformatics analysis

Background: Melanoma is an aggressive tumor caused by melanocytes characterized by a poor prognosis at the stage of metastasis. Therefore, it is crucial to identify biomarkers for progression and prognosis for the treatment of melanoma. Objectives: The study aimed to identify the specific genes related to the prognosis of melanoma utilizing bioinformatics analyses. Methods: Differentially expressed genes (DEGs) between melanoma tissues and normal tissues were screened from the GSE 3,189 gene expression profile of Gene Expression Omnibus (GEO). A co-expression network was constructed by weighted correlation network analysis (WGCNA). Functional enrichment analysis for DEGs was performed. The risk prognostic model and nomogram predictive model were established utilizing the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Results: Using the differential expression analysis and WGCNA, 1,408 DEGs were screened between melanoma tissues and normal tissues. Functional enrichment analysis proved that these genes primarily participated in the cell cycle and mitotic phase regulation in cancer. In addition, 17 optimal DEGs were identified for constructing the risk score prognostic model. Cox regression analysis further revealed that ectonucleotide pyrophosphatase/phosphodiesterase 4 (ENPP4) and FGR proto-oncogene, Src family tyrosine kinase (FGR) were the key genes significantly associated with survival. A nomogram prediction model was established for individual survival probability by integrating pathological T/N/M stage, age, ENPP4, and FGR. High FGR or ENPP4 expression indicated a better prognosis in melanoma patients. Conclusion: This study identified FGR and ENPP4 as potentially useful prognostic biomarkers for melanoma. The corresponding risk score prognostic model and nomogram may be a reliable tool for predicting the prognosis of melanoma patients.

PTPRC functions as a prognosis biomarker in the tumor microenvironment of cutaneous melanoma

Cutaneous melanoma is one of the most malignant types of skin cancer, with an extremely poor prognosis. Immune cells infiltrated in the tumor microenvironment (TME) affects melanoma initiation, progression, prognosis and immunotherapy strategies in melanoma. The potential utility of TME-related genes as a prognostic model for melanoma and as a predictor of immunotherapeutic response merits further exploration. In this study, we determined that an immune-related gene, protein tyrosine phosphatase receptor type C (PTPRC), was positively correlated with the positive prognosis of melanoma patients. Integration of this gene with TNM classification created a predictive model that showed better performance in determining overall survival than others. PTPRC expression was positively correlated with the levels of immune checkpoint molecules, and PTPRC knockdown significantly enhanced the migration, invasion, and proliferation of melanoma cells. Finally, immunohistochemical results from HPA and Real-time quantitative PCR of clinical tissues confirmed that PTPRC expression was higher in melanoma than in normal skin. In conclusion, PTPRC served as a potential predictor of survival and response to immunotherapy in melanoma patients. The risk model combining the PTPRC and TNM classifications holds the potential to be a promising tool for prognostic prediction of cutaneous melanoma. This will help in the effective clinical management of melanoma patients.

Melanoma patients with immune-related adverse events after immune checkpoint inhibitors are characterized by a distinct immunological phenotype of circulating T cells and M-MDSCs

ABSTRACT Treatment with immune checkpoint inhibitors (ICIs) has improved the prognosis of melanoma patients. However, ICIs can cause an overactivation of the immune system followed by diverse immunological side effects known as immune-related adverse events (irAE). Currently, the toxicity of irAE is limiting the usage of ICIs. Here, we studied circulating monocytic myeloid-derived suppressor cells (M-MDSCs) and T cells in course of irAE after the ICI therapy. Our longitudinal study involved 31 melanoma patients with and without adverse events during anti-PD-1 monotherapy or anti-CTLA-4/PD-1 combination therapy. Peripheral blood samples were analyzed before ICI start, during ICI treatment, at the time point of irAE and during immunosuppressive treatment to cure irAE. We observed an enhanced progression-free survival among patients with irAE. In patients with irAE, we found an upregulation of CD69 on CD8+ T cells and a decreased frequency of regulatory T cells (Tregs). Moreover, lower frequencies of Tregs correlated with more severe side effects. Patients treated with immunomodulatory drugs after irAE manifestation tend to show an elevated number of M-MDSCs during an immunosuppressive therapy. We suggest that an activation of CD8+ T cells and the reduction of Treg frequencies could be responsible for the development of irAE.

Plasma Thermogram Parameters Differentiate Status and Overall Survival of Melanoma Patients.

Melanoma is the fifth most common cancer in the United States and the deadliest of all skin cancers. Even with recent advancements in treatment, there is still a 13% two-year recurrence rate, with approximately 30% of recurrences being distant metastases. Identifying patients at high risk for recurrence or advanced disease is critical for optimal clinical decision-making. Currently, there is substantial variability in the selection of screening tests and imaging, with most modalities characterized by relatively low accuracy. In the current study, we built upon a preliminary examination of differential scanning calorimetry (DSC) in the melanoma setting to examine its utility for diagnostic and prognostic assessment. Using regression analysis, we found that selected DSC profile (thermogram) parameters were useful for differentiation between melanoma patients and healthy controls, with more complex models distinguishing melanoma patients with no evidence of disease from patients with active disease. Thermogram features contributing to the third principal component (PC3) were useful for differentiation between controls and melanoma patients, and Cox proportional hazards regression analysis indicated that PC3 was useful for predicting the overall survival of active melanoma patients. With the further development and optimization of the classification method, DSC could complement current diagnostic strategies to improve screening, diagnosis, and prognosis of melanoma patients.

Survival in patients with unresectable melanoma: To infinity and beyond?

e21504 Background: The introduction of checkpoint inhibitors and targeted treatment has led to significant improvements in prognosis for melanoma patients over the last years. We aimed to evaluate the survival per year of diagnosis. Methods: All systemically treated patients diagnosed with advanced melanoma from 2013 to 2021 were included from the nationwide Dutch Melanoma Treatment Registry. Baseline characteristics, overall survival (OS), and melanoma-specific survival (MSS) were compared between the different years of diagnosis of unresectable melanoma. Results: In total, 6324 patients were included. Over the years, the age at start of treatment gradually increased. Patients treated in 2020 and 2021 more often had an Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥2 and synchronous metastatic disease (table). The percentage of patients receiving systemic treatment did not change over the years. Median OS gradually increased from 11.3 months (95%CI 10.1-12.5) for patients diagnosed in 2013 to 33.3 months (95%CI 28.8-37.4) for patients diagnosed in 2019. Remarkably however, median OS was lower for patients diagnosed in 2020 and 2021 (24.8 months; 95%CI 21.1-28.2 and 18.8 months; 95%CI 17.6-NR). When excluding previously adjuvant-treated patients or looking at synchronous metastatic melanoma only, the same trends were seen. Similarly, differences in MSS mirrored our OS findings. Median OS and MSS can be found in the table. Conclusions: After a continuous survival improvement for advanced melanoma patients between 2013-2019, outcomes in 2020 and 2021 are remarkably poorer. The decreased performance status at the start of systemic treatment suggests that COVID-related delays might have played a role. [Table: see text]

A comprehensive signature based on endoplasmic reticulum stress-related genes in predicting prognosis and immunotherapy response in melanoma

Melanoma is considered as one of the most invasion types of skin cancer with high mortality rates. Although combination of immune checkpoint therapy with local surgical excision provide a novel promising therapeutic strategies, the overall prognosis of melanoma patients remains unsatisfactory. Endoplasmic reticulum (ER) stress, a process of protein misfolding and undue accumulation, has been proven to play an indispensable regulatory role in tumor progression and tumor immunity. However, whether the signature based ER genes has predictive value for the prognosis and immunotherapy of melanoma has not been systematically manifested. In this study, the LASSO regression and multivariate Cox regression were applied to construct a novel signature for predicting melanoma prognosis both in the training and testing set. Intriguingly, we found that patients endowed with high- and low-risk scores displayed differences in clinicopathologic classification, immune cell infiltration level, tumor microenvironment, and immune checkpoint treatment response. Subsequently, based on molecular biology experiments, we validated that silencing the expression of RAC1, an ERG composed of the risk signature, could restrain the proliferation and migration, promote apoptosis, as well as increase the expression of PD-1/PD-L1 and CTLA4 in melanoma cells. Taken together, the risk signature was regarded as promising predictors for melanoma prognosis and might provide prospective strategies to ameliorate patients’ response to immunotherapy.

External validation in an Australian population of the EORTC-DeCOG nomogram predicting recurrence, distant metastasis and overall mortality in melanoma patients with positive sentinel lymph nodes

BackgroundCalculating an accurate prognosis for melanoma patients who have a positive sentinel node (SN) biopsy is important both for them and for their treating doctors to guide decision-making, particularly when adjuvant systemic therapy is being considered. The recently published EORTC-DeCOG nomograms aim to provide this via an online portal that predicts 5-year rates for recurrence, distant metastasis and overall mortality. The present study provides external validation of these nomograms. Methods/MaterialsDe-identified data from patients with a positive SN biopsy between 2003 and 2015 were extracted from the prospectively maintained Melanoma Institute Australia (MIA) research database. ROC-curves with C-statistics, regression co-efficients and Decision Curve Net Benefit analyses were performed using the integrated private validation portal on the nomograms’ hosting platform (Evidencio). ResultsComplete data were available for 352 patients. The respective C-statistics for recurrence, distant metastasis and overall mortality nomogram validations were 0.68, 0.69 and 0.66. ConclusionThe performance of the nomograms in predicting recurrence and distant metastasis was similar in the MIA and the development populations, suggesting that they are robust. However, the overall mortality nomogram performance was significantly poorer in the MIA population (C-statistic 0.66) than in the original EORTC-DeCOG derivation cohort (C-statistic 0.70) and may therefore be less reliable for clinical use.

A BRAF mutation-associated gene risk model for predicting the prognosis of melanoma

BRAF mutation plays an important role in the pathogenesis and progression of melanoma and is correlated to the prognosis of melanoma patients. However, fewer studies have attempted to develop a BRAF mutation-associated gene risk model for predicting the prognosis of melanoma. The current research explores BRAF mutation-related biological features in melanoma and establishes a prognostic signature. First, we identified three significantly enriched KEGG pathways (glycosphingolipid biosynthesis - ganglio series, ether lipid metabolism, and glycosaminoglycan biosynthesis - keratan sulfate) and corresponding genes in the BRAF mutant group by gene set enrichment analysis. We then developed a prognostic signature based on 7 BRAF-associated genes (PLA2G2D, FUT8, PLA2G4E, PLA2G5, PLA2G1B, B3GNT2, and ST3GAL5) and assessed its prediction accuracy using ROC curve analysis. Finally, the nomogram was established according to the prognostic signature and independent clinical characteristics to predict the survival of melanoma patients. Furthermore, we found higher proportions of naive B cells, plasma cells, CD8 T cells, CD4 memory-activated T cells, and regulatory T cells in the low-risk group. Whereas lower proportions of M0, M1, and M2 macrophages and resting NK cells were observed in the high-risk group. The analysis also showed a significantly higher expression of immune checkpoint molecules (PD-1, PD-L1, CTLA4, BTLA, CD28, CD80, CD86, HAVCR2, ICOS, LAG3, and TIGIT) in the low-risk group. Our results provide novel insights into the effect of BRAF mutation on melanoma growth and indicate a promising direction toward immunotherapy and precision medicine in melanoma patients.

Abstract 3119: A novel tissue resident memory T cell (TRM) signature predicts prognosis and tumor microenvironment of patients with melanoma

Abstract Background: Melanoma is a prime example of how basic and translational research can improve cancer prognosis The tumor immune microenvironment (TIME) of melanoma is a dynamic, heterogeneous mixture of multiple immune cells and malignant and nonmalignant cells. Tissue resident memory T cells (TRM) may be prognostic for improved melanoma survival and proliferate during treatment with immune checkpoint inhibitors. The role of TRM in melanoma and rare melanoma subtypes is unknown. Method: Our goal was to examine the relationship between TRM abundance and melanoma prognosis. We generated TRM signatures using multiple independent single-cell RNA sequencing data from human melanoma cells to infer TRM abundance. Lastly, we built a LASSO Cox regression model that predicts patient survival. The TCGA dataset was used as a test group. Model accuracy was validated using Kaplan-Meier survival analysis, receiver operating characteristic curves, principal component analysis, and t-distributed stochastic neighbor embedding. Findings: We found a significantly longer overall survival in patients with high TRM infiltration. Furthermore, we found that TRM can interact with the tumor microenvironment and genomic features of melanoma, making TRM abundance positively correlate with the prognosis of melanoma patients. Melanoma abundance was also significantly associated with several common genomic aberrations, including the TP53 mutation. In addition, we developed a 20-gene risk score that significantly classifies patients into low- and high-risk categories. We found that in several independent datasets, patients with high risk scores had significantly worse overall survival than patients with low risk scores. Conclusions: Altogether, our findings suggest that TRM abundance may positively correlate with melanoma survival. We developed a high-precision LASSO Cox regression model based on the new TRM abundance characteristics. Our study shows that this model effectively predicts the prognosis of melanoma patients and may provide new therapeutic targets and measure the effectiveness of melanoma-directed therapies. Keywords: Tissue resident memory T cell, tumor immune microenvironment, melanoma, prognosis Citation Format: Chongming Jiang, Jianrong Li, Elena Helman, Xiling Shen, Chao Cheng. A novel tissue resident memory T cell (TRM) signature predicts prognosis and tumor microenvironment of patients with melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3119.

Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients.

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

Single-cell RNA analysis to identify five cytokines signaling in immune-related genes for melanoma survival prognosis.

Melanoma is one of the deadliest skin cancers. Recently, developed single-cell sequencing has revealed fresh insights into melanoma. Cytokine signaling in the immune system is crucial for tumor development in melanoma. To evaluate melanoma patient diagnosis and treatment, the prediction value of cytokine signaling in immune-related genes (CSIRGs) is needed. In this study, the machine learning method of least absolute selection and shrinkage operator (LASSO) regression was used to establish a CSIRG prognostic signature of melanoma at the single-cell level. We discovered a 5-CSIRG signature that was substantially related to the overall survival of melanoma patients. We also constructed a nomogram that combined CSIRGs and clinical features. Overall survival of melanoma patients can be consistently predicted with good performance as well as accuracy by both the 5-CSIRG signature and nomograms. We compared the melanoma patients in the CSIRG high- and low-risk groups in terms of tumor mutation burden, infiltration of the immune system, and gene enrichment. High CSIRG-risk patients had a lower tumor mutational burden than low CSIRG-risk patients. The CSIRG high-risk patients had a higher infiltration of monocytes. Signaling pathways including oxidative phosphorylation, DNA replication, and aminoacyl tRNA biosynthesis were enriched in the high-risk group. For the first time, we constructed and validated a machine-learning model by single-cell RNA-sequencing datasets that have the potential to be a novel treatment target and might serve as a prognostic biomarker panel for melanoma. The 5-CSIRG signature may assist in predicting melanoma patient prognosis, biological characteristics, and appropriate therapy.

Low expression of SEMA4D as a potential predictive molecular marker of poor survival in patients with melanoma combined with liver cancer.

This study explored the correlation between semaphorin 4D (SEMA4D) and the prognosis and survival time of patients with melanoma combined with liver cancer. A total of 272 patients were recruited, and clinical and follow-up data were recorded. The expression levels of SEMA4D and SEMA3B were determined. Pearson's χ2 test and Spearman's rank correlation coefficient were used to analyze the relationship between prognosis and the assessed parameters of melanoma patients. Univariate and multivariate Logistic regression and Cox proportional risk regression analyses were used for further analysis. Additionally, receiver operating characteristic curve and survival curves of subjects were plotted. The Pearson's χ2 test showed that the prognosis of melanoma patients was significantly correlated with age, tumor grade, and decreased SEMA4D expression. Additionally, Spearman's correlation coefficient analysis showed that age, tumor grade, and SEMA4D expression were significantly correlated with prognosis. Univariate logistic regression analysis showed that age and tumor grade, and SEMA4D expression, were significantly correlated with prognosis. Older patients, a higher tumor grade, and lower SEMA4D expression were associated with a poorer prognosis. Multivariate logistic regression analysis showed that older patients had a poorer prognosis, and patients with lower SEMA4D expression levels had a significantly worse prognosis than patients with higher SEMA4D expression levels. Kaplan-Meier analysis showed that the survival time of older patients was lower than that of the younger patients. The survival times of patients with lower SEMA4D expression levels were significantly lower than that of patients with higher SEMA4D expression levels. Multivariate Cox regression analysis showed that the survival time of older patients was lower than that of younger patients. The survival time of melanoma patients with low SEMA4D expression was significantly lower than that of patients with higher SEMA4D expression. SEMA4D was significantly associated with melanoma, and lower SEMA4D expression was associated with a poorer survival prognosis in melanoma patients.

NETO2 promotes melanoma progression via activation of the Ca2+/CaMKII signaling pathway.

Melanoma is the most aggressive cutaneous tumor. Neuropilin and tolloid-like 2 (NETO2) is closely related to tumorigenesis. However, the functional significance of NETO2 in melanoma progression remains unclear. Herein, we found that NETO2 expression was augmented in melanoma clinical tissues and associated with poor prognosis in melanoma patients. Disrupting NETO2 expression markedly inhibited melanoma proliferation, malignant growth, migration, and invasion by downregulating the levels of calcium ions (Ca2+) and the expression of key genes involved in the calcium signaling pathway. By contrast, NETO2 overexpression had the opposite effects. Importantly, pharmacological inhibition of CaMKII/CREB activity with the CaMKII inhibitor KN93 suppressed NETO2-induced proliferation and melanoma metastasis. Overall, this study uncovered the crucial role of NETO2-mediated regulation in melanoma progression, indicating that targeting NETO2 may effectively improve melanoma treatment.

CHRNA1 and its correlated-myogenesis/cell cycle genes are prognosis-related markers of metastatic melanoma

Nicotinic acetylcholine receptors (CHRNs) expression and their critical role in various types of cancer have been reported. However, it is still unclear which CHRNs and their associated genes play essential roles in metastasis in melanoma patients. Here, we performed bioinformatics analyses on publicly available bulk RNA sequencing (RNA-seq) data of patients with melanoma to identify the CHRNs highly expressed in metastatic melanoma. We found that CHRNA1 was highly expressed in metastatic melanoma samples compared to primary melanoma samples and was strongly associated with CHRNB1 and CHRNG. These muscle-type CHRNs (CHRNA1, CHRNB1, and CHRNG) were correlated with the ZEB1 and Rho/ROCK pathway-related genes in metastatic melanoma samples. Pairwise correlations and enrichment analyses revealed that CHRNA1 was significantly associated with myogenesis/muscle contraction and cell cycle genes. Kaplan-Meier curves illustrated the involvement of CHRNA1, four of its correlated genes (DES, FLNC, CDK1, and CDC20), and the myogenesis gene signature in the prognosis of melanoma patients. Following the bulk RNA-seq analysis, single-cell RNA-seq (scRNA-seq) analysis showed that the CHRNA1-expressing melanoma cells are primarily metastatic and had high expression levels of CHRNB1, CHRNG, and myogenesis/cell cycle-related genes. Our bioinformatics analyses of the bulk RNA-seq and scRNA-seq data of patients with melanoma revealed that CHRNA1 and its correlated myogenesis/cell-related cycle genes are critical prognosis-related markers of metastatic melanoma.

Suppression of exosomal hsa_circ_0001005 eliminates the Vemurafenib resistance of melanoma.

More and more evidences show that circular RNAs (circRNAs) can be used as miRNA sponge to regulate the drug resistance of malignancies, including melanoma. However, how exosomal circRNAs participate in the therapeutic resistance of melanoma remains ambiguous. Vemurafenib-resistant A375 cells were cultured and then the circRNA profile of exosomes from the parental A375 and A375-resistant cells were sequenced. Transmission electron microscopy (TEM), exogenous nanoparticle tracking analysis (NTA) and Western Blot assays were leveraged to confirm the successful collection of exosomes from A375 and A375R cells. Another five published RNA-seq data and microRNA-seq data, and seven miRNA databases were collected to construct a competing endogenous RNA (ceRNA) network. Comprehensive bioinformatic analysis was adopted to identify key molecules related to the drug resistance, including multiscale embedded gene co-expression network analysis (MEGENA). Then, qRT-PCR, cell viability and colony formation were used to estimate the function of hub circRNAs. The role of has_circ_0001005 in vivo was verified via xenograft assay. The Tumor online Prognostic analyses Platform (ToPP) was leveraged to develop the has_circ_0001005-related prognostic models for melanoma patients based on TCGA data. Compared with parental cells, hsa_circ_0001005 expression was significantly increased in resistant cells and their exosomes. The elevated level of hsa_circ_0001005 was related to the poor clinical prognosis of melanoma patients. Hsa_circ_0001005 found in melanoma was mainly secreted by drug-resistant cells as exosomes. Exosomal hsa_circ_0001005 activated multiple canonical pathways related to drug resistance through sponging four miRNAs, thus suppressing the drug sensitivity of melanoma. Knocking down hsa_circ_0001005 in vitro, we found that the inhibition of hsa_circ_0001005 could hinder the clone formation of melanoma. Further in vivo animal experiments suggested that suppression of hsa_circ_0001005 can increase the sensitivity to Vemurafenib of melanoma cells. Finally, we also constructed the functional regulatory ceRNA network and prognostic risk models for hsa_circ_0001005, and further survival analysis reveals that the regulatory network and prognostic risk models obviously affected the prognosis of melanoma patients. This study confirmed that the level of hsa_circ_0001005 in exosomes is the key factor affecting drug resistance of melanoma, which provides a new potential therapeutic target for melanoma patients.

Fibroblast growth factor receptor family mutations as a predictive biomarker for immune checkpoint inhibitors and its correlation with tumor immune microenvironment in melanoma.

The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the clinical outcomes of patients with metastatic melanoma. However, survival benefits are only observed in a subset of patients. The fibroblast growth factor receptor (FGFR) family genes are frequently mutated in melanoma, yet their impacts on the efficacy of ICIs remain unclear. Our study aimed to explore the association of FGFR mutations with ICIs efficacy in metastatic melanoma. The Cancer Genome Atlas (TCGA) data (PanCancer Atlas, skin cutaneous melanoma (SKCM), n = 448) in cBioPortal were collected as a TCGA cohort to investigate the association between FGFR mutations and prognosis of melanoma patients. To explore the impact of FGFR mutations on the efficacy of ICIs in melanoma, clinical and tumor whole-exome sequencing (WES) data of four ICI-treated studies from cBioPortal were consolidated as an ICIs-treated cohort. Moreover, the relationship between FGFR mutations and immunogenicity (tumor mutation burden (TMB), neo-antigen load (NAL), mismatch repair (MMR)-related genes and DNA damage repair (DDR)-related genes) of melanoma was evaluated utilizing data from the ICIs-treated cohort. The influence of FGFR mutations on the tumor immune microenvironment (TIME) of melanoma was also analyzed using the TCGA cohort. In the TCGA cohort, survival in melanoma patients with or without FGFR mutations was nearly equivalent. In the ICIs-treated cohort, patients with FGFR mutations had better survival than those without (median overall survival: 60.00 vs. 31.00 months; hazard ratio: 0.58, 95% CI: 0.42-0.80; P = 0.0051). Besides, the objective response rate was higher for patients harboring FGFR mutations (55.56%) compared to wild-type patients (22.40%) (P = 0.0076). Mechanistically, it was revealed that FGFR mutations correlated with increased immunogenicity (e.g., TMB, NAL, MMR-related gene mutations and DDR-related gene mutations). Meanwhile, FGFR mutant melanoma tended to exhibit an enhanced antitumor TIME compared with its wild-type counterparts. Our study demonstrated that FGFR mutations is a promising biomarker in stratifying patients with advanced melanoma who might benefit from ICIs therapy.

Circulating tumor DNA is a prognostic biomarker in metastatic melanoma patients treated with chemoimmunotherapy and BRAF inhibitor

Background Detectable circulating tumor DNA (ctDNA) has been associated with worse prognosis in melanoma patients. Material and methods We studied plasma ctDNA as a prognostic biomarker in 19 patients with metastatic melanoma and a detectable tumor mutation (13 BRAF, 5 NRAS, and 1 KRAS). Patients had received chemotherapy, interferon-alpha, and vemurafenib in a prospective clinical trial. Mutant allele frequency (MAF %) was determined with droplet digital PCR from pretreatment and sequential plasma samples. Results Higher pretreatment plasma ctDNA levels (MAF ≥3%) and detectable plasma ctDNA levels (MAF >0%) at the time of radiologically confirmed best objective response were associated with poor prognosis even when accounting for other relevant prognostic factors including performance status, tumor mutation, metastasis stage, and lactate dehydrogenase levels in multivariable analysis. Conclusion Higher pretreatment plasma ctDNA levels and sustained detectable plasma ctDNA levels during treatment indicated poor prognosis in metastatic melanoma patients.

Identification and validation of ferroptosis-related lncRNA signature as a prognostic model for skin cutaneous melanoma.

BackgroundMelanoma is a type of skin cancer, which originates from the malignant transformation of epidermal melanocytes, with extremely high lethality. Ferroptosis has been documented to be highly related to cancer pathogenesis and the effect of immunotherapy. In addition, the dysregulation of lncRNAs is greatly implicated in melanoma progression and ferroptosis regulation. However, the significance of ferroptosis-related lncRNA in melanoma treatment and the prognosis of melanoma patients remains elusive.Methods Via Least Absolute Shrinkage Selection Operator (LASSO) regression analysis in the TCGA SKCM database, a cutaneous melanoma risk model was established based on differentially-expressed ferroptosis-related lncRNAs (DEfrlncRNAs). The nomogram, receiver operating characteristic (ROC) curves, and calibration plots were conducted to examine the predictive performance of this model. Sequentially, we continued to analyze the differences between the high- and low-risk groups, in terms of clinical characteristics, immune cell infiltration, immune-related functions, and chemotherapy drug sensitivity. Moreover, the expressions of DEfrlncRNAs, PD-L1, and CD8 were also examined by qRT-PCR and immunohistochemical staining in melanoma tissues to further confirm the potential clinical implication of DEfrlncRNAs in melanoma immunotherapy.Results16 DEfrlncRNAs were identified, and a representative risk score for patient survival was constructed based on these 16 genes. The risk score was found to be an independent prognostic factor for the survival of melanoma patients. In addition, the low-risk group of patients had higher immune cell infiltration in the melanoma lesions, higher sensitivity to chemotherapeutic agents, and a better survival prognosis. Besides, the high expression of the identified 5 DEfrlncRNA in the low-risk group might suggest a higher possibility to benefit from immune checkpoint blockade therapy in the treatment of melanoma.ConclusionThe DEfrlncRNA risk prediction model related to ferroptosis genes can independently predict the prognosis of patients with melanoma and provide a basis for evaluating the response of clinical treatment in melanoma.

836P Outcome of PD-1 inhibitor therapy of advanced melanoma patients according to demographic factors in a real-world setting across Europe

Treatment with programmed cell death protein (PD-1) blocking antibodies substantially improves prognosis of melanoma patients. However, there is still limited evidence how baseline demographics influence treatment efficacy in real world practice.

Vitamin D deficiency in melanoma patients is associated with worse overall survival: a retrospective cohort study.

Recent interest has emerged in the protective role of vitamin D in melanoma survival and is the subject of multiple studies with heterogeneous results. Here, we present a retrospective cohort study of 264 patients with invasive melanoma from a tertiary university hospital. The aim of the study was to analyze the relationship between vitamin D levels and prognosis of melanoma patients. We found that lower vitamin D levels are independently associated with worse overall survival in melanoma patients in concordance with previous studies on other populations. Vitamin D deficiency could play a survival role in melanoma patients,. Future prospective studies are needed to investigate the effect of vitamin D supplementation on melanoma outcomes.